Barbieri Ruggero, Guryev Victor, Brandsma Corry-Anke, Suits Frank, Bischoff Rainer, Horvatovich Peter
Department of Gastroenterology and Hepatology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
European Research Institute for the Biology of Ageing, University Medical Center Groningen, Antonius Deusinglaan 1, 9713 AV, Groningen, The Netherlands.
Adv Exp Med Biol. 2016;926:21-47. doi: 10.1007/978-3-319-42316-6_3.
Proteogenomics is a multi-omics research field that has the aim to efficiently integrate genomics, transcriptomics and proteomics. With this approach it is possible to identify new patient-specific proteoforms that may have implications in disease development, specifically in cancer. Understanding the impact of a large number of mutations detected at the genomics level is needed to assess the effects at the proteome level. Proteogenomics data integration would help in identifying molecular changes that are persistent across multiple molecular layers and enable better interpretation of molecular mechanisms of disease, such as the causal relationship between single nucleotide polymorphisms (SNPs) and the expression of transcripts and translation of proteins compared to mainstream proteomics approaches. Identifying patient-specific protein forms and getting a better picture of molecular mechanisms of disease opens the avenue for precision and personalized medicine. Proteogenomics is, however, a challenging interdisciplinary science that requires the understanding of sample preparation, data acquisition and processing for genomics, transcriptomics and proteomics. This chapter aims to guide the reader through the technology and bioinformatics aspects of these multi-omics approaches, illustrated with proteogenomics applications having clinical or biological relevance.
蛋白质基因组学是一个多组学研究领域,旨在有效整合基因组学、转录组学和蛋白质组学。通过这种方法,可以识别可能对疾病发展,特别是癌症发展有影响的新的患者特异性蛋白变体。需要了解在基因组水平检测到的大量突变的影响,以评估蛋白质组水平的效应。与主流蛋白质组学方法相比,蛋白质基因组学数据整合将有助于识别跨多个分子层持续存在的分子变化,并能更好地解释疾病的分子机制,如单核苷酸多态性(SNP)与转录本表达和蛋白质翻译之间的因果关系。识别患者特异性蛋白质形式并更好地了解疾病的分子机制为精准和个性化医学开辟了道路。然而,蛋白质基因组学是一门具有挑战性的跨学科科学,需要了解基因组学、转录组学和蛋白质组学的样品制备、数据采集和处理。本章旨在引导读者了解这些多组学方法的技术和生物信息学方面,并通过具有临床或生物学相关性的蛋白质基因组学应用进行说明。